表面增强拉曼光谱分析用于比较乙型肝炎和丙型肝炎的 PCR 产物。
Surface-enhanced Raman spectral analysis for comparison of PCR products of hepatitis B and hepatitis C.
机构信息
Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38040, Pakistan.
Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38040, Pakistan.
出版信息
Photodiagnosis Photodyn Ther. 2021 Sep;35:102440. doi: 10.1016/j.pdpdt.2021.102440. Epub 2021 Jul 16.
BACKGROUND
Surface-enhanced Raman spectroscopy is a reliable tool for identification and differentiation of two diseases showing similar symptoms, hepatitis B (HBV) and hepatitis C (HCV).
OBJECTIVES
To develop a polymerase chain reaction technique (PCR) based SERS technique for differentiation of two human pathological conditions sharing the same symptoms using multivariate data analysis techniques e.g. principle component analysis (PCA) and partial least square discriminate analysis (PLS-DA).
METHODS
PCR products of HBV and HCV were differentiated by SERS using silver nanoparticles (AgNPs) as a SERS substrate. For this analysis, PCR products of both the diseases with predetermined viral loads were collected and analyzed under SERS instrument and unique SERS spectra of HBV and HCV was compared showing many differences at various points. Diseased classes of HBV and HCV and their negative control classes (viral load less than 1) were compared. PCR products of true healthy DNA and RNA were also compared, which were significantly separated. Moreover, SERS data was analyzed using multivariate data analysis techniques including principle component analysis (PCA) and partial least square discriminate analysis (PLS-DA) and differences were so prominent to observe.
RESULTS
SERS spectral data of HBV and HCV showed clear differences and were significantly separated using PCA. Negative control samples of both disorders and their true healthy samples of DNA and RNA were separated according to 1 principle component. By analyzing data using partial least square discriminate analysis, differentiation of two disease classes was considered more valid with sensitivity, specificity and accuracy value of 96%, 94% and 98% respectively. Value of area under curve (AUROC) was 0.7527.
CONCLUSION
SERS can be employed for identification and comparison of two human pathological conditions sharing the same symptomology.
背景
表面增强拉曼光谱是一种可靠的工具，可用于识别和区分两种具有相似症状的疾病，乙型肝炎（HBV）和丙型肝炎（HCV）。
目的
开发一种基于聚合酶链反应技术（PCR）的 SERS 技术，使用多元数据分析技术（如主成分分析（PCA）和偏最小二乘判别分析（PLS-DA））区分两种具有相同症状的人类病理状况。
方法
使用银纳米粒子（AgNPs）作为 SERS 基底，通过 SERS 区分 HBV 和 HCV 的 PCR 产物。为此分析，收集了两种疾病具有预定病毒载量的 PCR 产物，并在 SERS 仪器下进行分析，比较了 HBV 和 HCV 的独特 SERS 光谱，显示了许多在不同点的差异。比较了 HBV 和 HCV 的疾病类别及其阴性对照类别（病毒载量小于 1）。还比较了真正健康的 DNA 和 RNA 的 PCR 产物，它们明显分离。此外，使用多元数据分析技术（包括主成分分析（PCA）和偏最小二乘判别分析（PLS-DA））对 SERS 数据进行了分析，差异非常明显。
结果
HBV 和 HCV 的 SERS 光谱数据显示出明显的差异，并使用 PCA 进行了明显的分离。两种疾病的阴性对照样本及其真正健康的 DNA 和 RNA 样本根据 1 个主成分分离。通过使用偏最小二乘判别分析分析数据，两种疾病类别的区分被认为更有效，灵敏度、特异性和准确度分别为 96%、94%和 98%。曲线下面积（AUROC）的值为 0.7527。
结论
SERS 可用于识别和比较两种具有相同症状的人类病理状况。
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